Lesson 5: 4.5 Observational Studies and Experiments
Duration of Days: 2
Lesson Objective
Students will be able to distinguish between observational studies and experiments and explain why only well-designed experiments can establish a cause-and-effect relationship.
If we observe that people who exercise more have lower blood pressure, can we say exercise causes lower blood pressure?
What is a "confounding variable," and how does it act like a "hidden ghost" in our data?
Observational study
Experiment
Confounding
Treatment
Experimental units / Subjects
Factors / Levels
HSS-IC.B.3: Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.
The SAT often presents a study and asks, "Which of the following is a valid conclusion?" Students must remember: If it’s an observational study, you can only conclude an association. If it’s a randomized experiment, you can conclude causation.
This section draws a hard line in the sand. It explains that in an observational study, we don't control the environment, which allows "confounding variables" to mix with our results. Experiments are designed to "isolate" the variable we care about.
The Problem: A study found that people who use night-lights in their children's rooms are more likely to have children who are nearsighted.
Task: Is this an experiment? Identify a potential confounding variable that might explain this link without the night-light being the cause.
The Cause-and-Effect Trap: Students want to jump to "why" something happened. They need to be trained to ask, "Was there random assignment?" before using the word "cause."
Use a "Confounding Web" visual where the explanatory and response variables are connected, but a third "lurking" variable points to both.
Teacher assigns examples from the textbook and other resources.
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